Differential diagnosis between Parkinson’s disease and Multiple System Atrophy using digital speech analysis
Main issues and objectives
Parkinson’s disease (PD) and multiple system atrophy (MSA) are neurodegenerative disorders. The latter belongs to the group of atypical parkinsonian disorders and has a poor prognosis. In early stages of the disease, PD and MSA symptoms are very similar, particularly in MSA-P patients where parkinsonism predominates. The differential diagnosis between MSA-P and PD can be very challenging in early disease stages, while early diagnostic certitude is important for the patient because of the diverging prognosis. Indeed, despite recent efforts, no validated objective marker is currently available to guide the clinician in this differential diagnosis. The need of such markers is hence very high in the neurology community, particularly given the severity of the prognosis of MSA-P.
The innovative goal of our project is two-fold, i.e. to develop a non-invasive objective digital marker to assist in the early differential diagnosis between PD and MSA-P, and the diagnosis of PD compared to healthy controls (HC). This would be a world premiere as we would be the first scientists to achieve such an important contribution in the field of clinical diagnosis of neurodegenerative diseases. Moreover, our ambition is to develop a very low cost and portable digital tool. In case of success, this would allow a large scale and world-wide use; every neurologist would have the possibility to use the digital marker in his clinic or private office.
The originality of our project stands in the methodology we adopt to achieve its innovative and ambitious goal. Indeed, speech impairment, commonly called dysarthria, is a common early symptom in both diseases and of different origin. Our approach is to use dysarthria, through a digital processing of voice recordings of patients, as a vehicle to distinguish between PD and MSA-P, and between PD and HC, in early disease stages. This topic is an emerging research field with several teams around the world working on the discrimination between PD and HC based on voice recordings.
The ambition and the originality of this project is thus to develop a digital voice-based tool for objective discrimination between PD and MSA-P, and between PD and HC. Such innovation would have significant benefits at different levels: clinical, scientific, technological, economical and societal.
- Khalid Daoudi (coordinator) : INRIA Bordeaux
- Wassilios Meissner : CHU Bordeaux
- Anne Pavy-le-Traon : CHU Toulouse
- Sébastien Dejean et Laurent Risser : UPS Toulouse
People involved in the SAMOVA team
- Julie Mauclair (scientific coordinator)
- Jérôme Farinas
- Régine André-Obrecht
- Julien Pinquier
- Etienne Sicard
- Agence Nationale Recherche PRC 2016
- Start time : 1st november 2016
- End time : 30th avril 2020